scmamp (version 0.2.3)

multipleComparisonTest: Tests for multiple comparisons

Description

This function is a wrapper to multiple comparison tests.

Usage

multipleComparisonTest(data, algorithms = NULL, group.by = NULL,
  test = "aligned ranks", correct = "finner", alpha = 0.05, ...)

Arguments

data

A matrix or data frame containing the results obtained by the algorithms (columns) in each problem (rows). It can contain additional columns, but if any of the column has to be discarderd (not used neither to group the problems nor to be part of the compa

algorithms

Vector with either the names or the indices of the columns that contain the values to be tested. If not provided, the function assumes that all the columns except those indicated in group.by represent the results obtained by an algorithm.

group.by

Vector with either the names or the indices of the columns to be used to group the data. Each group is tested independently. If NULL, all the data is used for a single comparison.

test

Parameter that indicates the statistical test to be used. It can be either a string indicating one of the available test or a function. As a string, it can take the following values:

• 'friedman'- Friedman test, as in Garcia and Herrer

Value

• In case the group.by argument is not provided (or it is NULL), the function return an object of class htest. If columns for grouping are provided, then the function returns a matrix that includes, for each group, the values of the group.by columns, the raw p-value and the corrected p-value.

  #'

item

• correct
• finner - Finner's procedure, as in Garcia and Herrera (2010)
• rom - Rom's procedure, as in Garcia and Herrera (2010)
• li - Li's procedure, as in Garcia and Herrera (2010)
• Any of the methods implemented in the p.adjust function. For a list of options, type p.adjust.methods
• alpha
• ...

itemize

• holland- Holland's procedure, as in Garcia and Herrera (2010)

emph

in the same order

References

S. Garcia and F. Herrera (2010) Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and ata mining: Experimental analysis of power. Information Sciences, 180, 2044-2064.

Kanji, G. K. (2006) 100 Statistical Tests. SAGE Publications Ltd, 3rd edition.

See Also

friedmanTest, friedmanAlignedRanksTest, quadeTest, anovaTest, adjustShaffer, adjustBergmannHommel, adjustHolland, adjustFinner, adjustRom, adjustLi

Examples

# Grouped data
data(data_blum_2015)
multipleComparisonTest (data=data.blum.2015,
                        algorithms=c("FrogCOL", "FrogMIS", "FruitFly"),
                        group.by=c("Size", "Radius"),
                        test="quade", correct="finner")
# Not grouped data
data(data_gh_2008)
multipleComparisonTest (data=data.gh.2008, test="aligned ranks",
                        correct="hochberg")